When AI shifts from assistance to execution in credit
Now, AI is moving from an assistant to an operator.
Srijan Nagar
The SME squeeze and the quiet jobs AI does for Fintech
SMEs in India do remarkable things with limited oxygen. This one is for lenders who want clarity, SMEs who want a breathing room, and anyone tired of hearing about AI without hearing how it helps.
What Apple's AI strategy signals for FinTech platforms
The race to build the best AI model is quickly becoming less important than the race to build the best product around AI.
How AI became the engine of modern finance in 2025
AI has officially and authoritatively moved from our newsfeeds to our daily workflows.
The journey is the policy - Rethinking digital lending for 2026 and beyond
I've started noticing a quiet shift in the digital lending landscape over the past year.
The $1 trillion blind spot: Why AI is India's FinTech security nightmare
With India seeing a 67% spike in digital fraud losses, the 'business as usual' approach to cybersecurity is officially obsolete.
Financial Services Has a New Fraud Problem: AI That Looks Too Real
I spent some time last week staring at two restaurant receipts. Both were of the same amount. Both
From embedded to generative: Charting credit's fourth reset
From embedded to generative: Charting credit's fourth reset
How will AI evolve partnership lending in India?
Partnership lending has the rails--apps, UPI, marketplaces. Read how AI can act as the orchestrator in the partnership lending value chain.
Can RBI really afford to go all-in on AI in finance?
RBI's new 'tolerant supervisory stance' for AI is a stark departure from its usual hawkish stance. Read now to discover what this could mean for India's financial future.
Why lenders should bet on AI-based automation, not decisions
Indian finance should focus on AI automation over lending decisions. Learn why data quality issues make operational AI the smart choice for NBFCs and banks.
How AI caught 40,000 taxpayers and what it means for digital lending
But this year, 40,000 taxpayers suddenly needed to file corrections, withdrawing ₹1,045 crore worth of deductions they had claimed.